Objective:

Although associations between ambient air pollution and acute cardiorespiratory outcomes have been observed in numerous studies, questions remain about the degree to which these findings are generalizable between locations and whether the observed health effects are due to the individual pollutants measured or to pollutants acting in combination with other pollutants. In Project 4, we conducted a multi-city time-series study to clarify the impacts of air quality on acute cardiorespiratory morbidity in five U.S. cities (Atlanta, GA; Birmingham, AL; Dallas, TX; Pittsburgh, PA; St. Louis, IL-MO) using novel mixture characterization metrics. Analyses included consideration of factors related to air pollution mixtures, exposure measurement error, concentration-response functions, population susceptibility and vulnerability, and seasonality and climate to help explain heterogeneity in short-term associations between air quality measures and cardiorespiratory emergency department (ED) visits.

Summary/Accomplishments (Outputs/Outcomes):

Project 4 combined multi-year data on ambient mixture characterization methods and ED visits in five cities. Epidemiologic analyses focused on the following six areas:

2. Exposure assignment approaches for large study areas.Population-based studies such as Project 4 relate day-to-day changes in ambient concentrations, often estimated using measurements made at ambient monitoring stations, to indicators of population health for a community, such as daily counts of deaths or ED visits. The exposure and health data in these studies are often misaligned in space, leading to concerns of bias in health effect estimates due to exposure measurement error. Such measurement error arises when the exposure measure does not capture the true average exposure of all at-risk individuals in the study area. In SCAPE, we documented and described the impacts of such measurement error through a series of early publications (Goldman, et al., 2011, 2012; Strickland, et al., 2011; Sarnat, et al., 2013). We then developed a data fusion approach that combines observational data from monitors and outputs from the Community Multiscale Air Quality (CMAQ) model (Friberg, et al., 2016; Friberg, et al., accepted) to estimate population exposure for Project 4 cities that aimed to better represent exposure for a range of pollutants across cities than use of monitoring data alone. Applied in epidemiologic analyses, we found that use of the data fusion metrics led to stronger health effect estimates compared to use of central monitoring site data across cities, particularly for spatiotemporally heterogeneous pollutants such as NO2 and SO2 (Sarnat, et al., ISEE 2015). The results provide a qualitative indication of reduced exposure measurement error for the data fusion exposure metric and indicate the importance of exposure assignment approach in large study areas.

3. Concentration-response (CR) function shape. Linearity in CR function shape for ambient pollutants and acute health outcomes often is assumed. In many cases, however, the assumption of linearity is made due to practical reasons, such as for ease of modeling linear relationships and ease of interpretation of parameter estimates. However, if the relationship is truly non-linear but modeled linearly, measures of association for particular pollution levels may be over or underestimated. Inaccurate risk estimates may have intervention and policy implications, and can impact comparisons of risk estimates across cities with different pollution levels. Here, we used Project 4 as a platform for specifically evaluating CR function shapes for O3 and respiratory ED visits in multiple cities under different model assumptions (linear, linear-threshold, quadratic, cubic, categorical, and cubic spline) (Barry, et al., ISEE 2016). O3 was positively associated with respiratory ED visits overall as well as with ED visits for asthma and upper respiratory infections in all models. Cubic and cubic spline functions best described the O3-respiratory disease relationship in all five cities; however, linear results were similar for O3 less than 60 ppb. Assessing CR function shape before analyzing and interpreting data can provide an idea as to which model assumptions may be most accurate for the specific study, city, and outcome.

4. Susceptible and vulnerable populations. Susceptibility to the health effects of ambient pollution may be influenced by both intrinsic factors, such as age and sex, and extrinsic factors, such as neighborhood socioeconomic status (SES). In Project 4, we conducted epidemiologic analyses to better understand the potential for these factors to confer susceptibility and vulnerability to ambient pollution, with a focus on respiratory health. Our findings suggest that age is a susceptibility factor for asthma exacerbations in response to air pollution, with school-age children having the highest susceptibility; strong observed associations among 5-18 year olds appeared to be partially driven by non-white and male patients, suggesting race/ethnicity and sex to be further factors conferring susceptibility (Alhanti, et al., 2016). In additional analyses focused on pediatric respiratory health, we found that neighborhood-level SES is a further factor contributing vulnerability to air pollution-related childhood morbidity (O’Lenick, et al., 2017a, 2017c). Children living in low SES environments appear to be especially vulnerable given positive health effect estimates and high underlying respiratory ED visit rates. We determined that inconsistent findings of effect modification by neighborhood SES among previous similar studies may be partially explained by choice of SES stratification criteria, and the use of multiplicative models combined with differing baseline risk across SES populations. Ongoing analyses are considering factors conferring susceptibility and vulnerability to the cardiovascular health effects of air pollution.

5. Ambient temperature as a main effect.Climate change is expected to cause higher ambient temperatures, especially in urban environments. Exposure to high ambient temperature may result in various adverse effects. In conjunction with funding from the National Institutes of Health, we conducted an investigation of the impacts of high temperatures and heat waves on ED visits for a broad range of ED visit outcomes in Atlanta (Winquist, et al., 2016; Heidari, et al., 2016; Chen, et al., 2017; O’Lenick, et al., 2017b). In main analyses, we observed associations between daily ambient maximum temperature and apparent temperature and ED visits for all internal causes, heat illness, fluid and electrolyte imbalances, renal diseases, cardiovascular diseases, asthma, diabetes, and intestinal infections (Winquist, et al., 2016). Age groups with the strongest observed associations were 65+ years for all internal causes and diabetes; 19-64 years for fluid and electrolyte imbalances and renal disease; and 5-18 years for asthma and intestinal infections. Based on these results, we concluded that optimal interventions and health-impact projections should account for varying heat-health impacts across ages. In further analyses, we examined the added effect of extreme heat over a sustained period beyond the continuous temperature-response relationships (Chen, et al., 2017). Our results suggest that prolonged heat exposure can confer added adverse health impacts beyond the risk due to higher daily temperature, particularly for renal diseases, cardiovascular diseases, and intestinal infection. We found some evidence that longer heat wave duration, later timing in the year, and higher heat wave intensity were associated with higher risks. We also found that associations of heat waves with ED visits were sensitive to heat wave definitions, which may be a result of different heat wave metrics representing different heat stress characteristics. Specifically, we concluded that minimum or nighttime temperatures also may be useful to consider in heat warning systems for some health outcomes.

6. Ambient temperature as a modifier of air pollution effects. We assessed modification of the acute respiratory effects of ambient air pollution by ambient temperature using splines to allow for nonlinearity in effect modification across multiple cities (Darrow, et al., ISEE 2016). Results suggest associations of ambient air pollution and acute respiratory outcomes vary by ambient temperatures, with higher estimated effects when mean ambient temperatures are mild compared to colder or warmer temperatures. These findings may reflect higher exposure to ambient pollution via increased time spent outdoors and/or higher air exchange rates (e.g., due to use of windows for ventilation, less A/C). Ongoing analyses are assessing estimated residential air exchange rates as a modifier of air pollution health associations (Sarnat, et al., 2013; Liang, et al., ISEE 2016).

Conclusions:

In Project 4, we observed associations of major ambient pollutants and specific air pollution mixtures and cardiorespiratory ED visits across several U.S. cities. Specifically, mixtures related to O3, secondary organic aerosols, biomass burning, and traffic combustion-related pollution appeared to have impacts on respiratory morbidity; and primary traffic-related pollution mixtures (both tailpipe, combustion-related components as well as tire wear/brake pad related components) were found to be important for cardiovascular morbidity. High ambient temperatures, expressed either as continuous warm-season temperatures or heat waves, were found to have strong impacts on acute morbidity, particularly dehydration and kidney-related outcomes, but also cardiorespiratory morbidity. Heat as an ambient exposure may be important to consider in the broad context of assessing health impacts of atmospheric mixtures. Finally, we found sociodemographic factors (age and SES) to be important modifiers of air pollution and temperature-related health associations. New work extending this research in additional cities with sufficiently resolved air quality data will contribute to better characterizing the generalizability of these findings.

Main Center Abstract and Reports:

Subprojects under this Center:(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).R834799C001 Development and Deployment of an Instrumentation Suite for Comprehensive Air Quality Characterization Including Aerosol ROSR834799C002 Examining In-Vehicle Pollution and Oxidative Stress in a Cohort of Daily CommutersR834799C003 Novel Estimates of Pollutant Mixtures and Pediatric Health in Two Birth CohortsR834799C004 A Multi-City Time-Series Study of Pollutant Mixtures and Acute Morbidity

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.